Textile-Sensing Wearable Systems for Continuous Motion Angle Estimation: A Systematic Review

Abstract

Textile sensors have demonstrated significant potential in next-generation wearable systems due to their excellent performance and unobtrusive nature. By building specialized sensing networks and algorithms, textile-based wearable systems can estimate the continuous motion angles of human joints with desirable accuracies. This article offers a systematic review aimed at identifying key challenges in this field and encouraging further applications of textile strain sensor networks within the human–computer interaction (HCI) community. To achieve this, we conducted an exhaustive literature search across four major databases: IEEE Xplore, PubMed, Scopus, and Web of Science, spanning from January 2016 to August 2023. Applying inclusion and exclusion criteria, we narrowed down 2684 results to a total of 24 relevant papers. To analyze these studies, we proposed a framework that incorporates both technical aspects – such as textile strain sensors, sensor placement, algorithms, and technical evaluations – and contextual factors like target users, wearability, and application scenarios. Our analysis uncovered two critical research gaps: First, it exists an incongruity between the development of textile-based wearables and the advancements in textile sensors. Second, there is a noticeable absence of contextual design considerations in this specific domain. To address these issues, we offer discussions and recommendations from three perspectives: 1) enhancing the robustness of textile-sensing networks, 2) improving wearability, and 3) expanding application scenarios.

Keywords:

• Textile sensing network
• joint angle estimation
• motion monitoring
• wearable technology

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project was funded by the Natural Science Foundation of China (62202335) and the Science and Technology Commission of Shanghai Municipality (20YF1451200).

Notes on contributors

Runhua Zhang

Runhua Zhang received her Bachelor of Engineering degree from Sichuan University, China, in 2021. She is currently a graduate student at the College of Design and Innovation, Tongji University, Shanghai, China. Her research interests encompass Human-Computer Interaction, health informatics and wearable technology.

Leheng Chen

Leheng Chen received his Bachelor of Engineering degree from Tongji University, Shanghai, China, in 2020. He is currently a graduate student at the College of Design and Innovation, Tongji University, Shanghai, China. His research interests encompass Human-AI Cooperation and wearable technology.

Yuanda Hu

Yuanda Hu is currently pursuing PhD degree at the College of Design and Innovation, Tongji University, Shanghai, China. His research interests include human-robot interaction, wearable technology, and pattern recognition.

Yueyao Zhang

Yueyao Zhang received her Bachelor degree from Wuhan University and obtained her master’s degree from Tongji University. Her research focuses on the layout theory and tool development of intelligent textile sensors.

Jiayi Chen

Jiayi Chen is a graduate student at the College of Design and Innovation, Tongji University, Shanghai, China. Her research interests involve sustainable human–computer interaction and wearable technology.

Tianzhan Liang

Tianzhan Liang received his Bachelor of Engineering degree from Hefei University of Technology in 2018. He is currently a graduate student at the College of Design and Innovation, Tongji University, Shanghai, China. His research interests include augmented reality, virtual reality, and wearable technology.

Xiaohua Sun

Xiaohua Sun is a professor at the College of Design and Innovation, Tongji University, China. She received her Ph.D. degree in Design and Computation from Massachusetts Institute of Technology in 2007. Her research interests include human–robot interaction (HRI), smart healthcare and rehabilitation, and extended reality (XR), etc.

Qi Wang

Qi Wang received her Ph.D. degree from the Eindhoven University of Technology (Tu/e). She is currently an associate professor in the College of Design and Innovation, Tongji University. Her main research focused on wearable systems based on smart textiles for health.